SBIR Phase I research demonstrated the feasibility of using Color Computer Vision and Neural Network technologies (hereafter referred to as "Neural Technologies") in classifying white blood cells. SBIR Phase II research effort seeks to develop an instrument that fully automates the microscopic differential count using Neural Technologies. Despite the wide use of flow cytometry differential counters, there are in excess of 100 million microscopic differential counts performed annually in the United States. An instrument that automates this procedure is needed to improve its accuracy and consistency in the diagnosis and monitoring of abnormal leukocytes. The accurate and consistent classification of abnormal white cells (i.e. myelocytes, variant lymphocytes, blasts, etc.) will greatly improve the ability to monitor patients' progress during treatment (chemotherapy, radiation, etc.). Automation of the leukocyte differential is also needed to help counter the growing shortage of Technologists and the associated delays in test reporting. In Phase II SBIR studies, the accuracy and consistency of Neural Technologies in classifying normal and abnormal cells seen in bone marrow smears will also be evaluated. The automation of other microscopic procedures not involving blood cells (Pap smears, tissue sections, etc.) is possible using Neural Technologies and will be the subject of subsequent investigations.